A Markov process can be used to model a random system that changes states according to a transition rule that only depends on the current state. And the Markov property is the most important property during Markov process, namely the conditional probability distribution of the future states of the process depends only upon the present state[1]}, [2]}, [3]}. Markov chain is a stochastic process with Markov property[4]}. It is widely used in many applications[5]}, [6]}, [7]}, [8]}, especially in the prediction[9]}, [10]}, such as rainfall prediction[11]}, [12]}, economy prediction[13]}, [14]} and so on.
